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Article: Two-stage approach for machine-part grouping and cell layout problems

TitleTwo-stage approach for machine-part grouping and cell layout problems
Authors
KeywordsCell layout problem
Genetic algorithms
Machine-part grouping problem
Operational sequence
Sequencing
Issue Date2006
PublisherPergamon. The Journal's web site is located at http://www.elsevier.com/locate/rcim
Citation
Robotics And Computer-Integrated Manufacturing, 2006, v. 22 n. 3, p. 217-238 How to Cite?
AbstractCellular manufacturing system (CMS) which is based on the concept of group technology (GT) has been recognized as an efficient and effective way to improve the productivity in a factory. In recent years, there have been continuous research efforts to study different facet of CMS. Most of them concentrated on distinguishing the part families and machine cells either simultaneously or individually with the objective of minimizing intercellular and intracellular part movements. This is known as machine-part grouping problem (MPGP) which is a crucial process while designing CMS. Nevertheless, in reality some components may not be finished within only one cell, they have to travel to another cell(s) for further operation(s). Under this circumstance, intercellular part movement will occur. Different order/sequence of machine cells allocation may result in different total intercellular movement distance unit. It should be noted that if the production volume of each part is very large, then the total number of intercellular movement will be further larger. Therefore, the sequence of machine cells is particularly important in this aspect. With this consideration, the main aim of this work is to propose two-stage approach for solving cell formation problem as well as cell layout problem. The first stage is to identify machine cells and part families, which is the essential part of MPGP. The work in second stage is to carry out a macro-approach to study the cell formation problem with consideration of machining sequence. The impact of the sequencing for allocating the machine cells on minimizing intercellular movement distance unit will be investigated in this stage. The problem scope, which is a MPGP together with the background of cell layout problem (CLP), has been identified. Two mathematical models are formulated for MPGP and CLP respectively. The primary assumption of CLP is that it is a linear layout. The CLP is considered as a quadratic assignment problem (QAP). As MPGP and QAP are NP-hard, genetic algorithm (GA) is employed as solving algorithm. GA is a popular heuristic search technique and has proved superior performance on complex optimization problem. In addition, an industrial case study of a steel member production company has been employed to evaluate the proposed MPGP and CLP models, and the computational results are presented. © 2005 Elsevier Ltd. All rights reserved.
Persistent Identifierhttp://hdl.handle.net/10722/74481
ISSN
2015 Impact Factor: 2.077
2015 SCImago Journal Rankings: 1.621
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorChan, FTSen_HK
dc.contributor.authorLau, KWen_HK
dc.contributor.authorChan, PLYen_HK
dc.contributor.authorChoy, KLen_HK
dc.date.accessioned2010-09-06T07:01:45Z-
dc.date.available2010-09-06T07:01:45Z-
dc.date.issued2006en_HK
dc.identifier.citationRobotics And Computer-Integrated Manufacturing, 2006, v. 22 n. 3, p. 217-238en_HK
dc.identifier.issn0736-5845en_HK
dc.identifier.urihttp://hdl.handle.net/10722/74481-
dc.description.abstractCellular manufacturing system (CMS) which is based on the concept of group technology (GT) has been recognized as an efficient and effective way to improve the productivity in a factory. In recent years, there have been continuous research efforts to study different facet of CMS. Most of them concentrated on distinguishing the part families and machine cells either simultaneously or individually with the objective of minimizing intercellular and intracellular part movements. This is known as machine-part grouping problem (MPGP) which is a crucial process while designing CMS. Nevertheless, in reality some components may not be finished within only one cell, they have to travel to another cell(s) for further operation(s). Under this circumstance, intercellular part movement will occur. Different order/sequence of machine cells allocation may result in different total intercellular movement distance unit. It should be noted that if the production volume of each part is very large, then the total number of intercellular movement will be further larger. Therefore, the sequence of machine cells is particularly important in this aspect. With this consideration, the main aim of this work is to propose two-stage approach for solving cell formation problem as well as cell layout problem. The first stage is to identify machine cells and part families, which is the essential part of MPGP. The work in second stage is to carry out a macro-approach to study the cell formation problem with consideration of machining sequence. The impact of the sequencing for allocating the machine cells on minimizing intercellular movement distance unit will be investigated in this stage. The problem scope, which is a MPGP together with the background of cell layout problem (CLP), has been identified. Two mathematical models are formulated for MPGP and CLP respectively. The primary assumption of CLP is that it is a linear layout. The CLP is considered as a quadratic assignment problem (QAP). As MPGP and QAP are NP-hard, genetic algorithm (GA) is employed as solving algorithm. GA is a popular heuristic search technique and has proved superior performance on complex optimization problem. In addition, an industrial case study of a steel member production company has been employed to evaluate the proposed MPGP and CLP models, and the computational results are presented. © 2005 Elsevier Ltd. All rights reserved.en_HK
dc.languageengen_HK
dc.publisherPergamon. The Journal's web site is located at http://www.elsevier.com/locate/rcimen_HK
dc.relation.ispartofRobotics and Computer-Integrated Manufacturingen_HK
dc.subjectCell layout problemen_HK
dc.subjectGenetic algorithmsen_HK
dc.subjectMachine-part grouping problemen_HK
dc.subjectOperational sequenceen_HK
dc.subjectSequencingen_HK
dc.titleTwo-stage approach for machine-part grouping and cell layout problemsen_HK
dc.typeArticleen_HK
dc.identifier.emailChan, FTS: ftschan@hkucc.hku.hken_HK
dc.identifier.emailChan, PLY: plychan@hku.hken_HK
dc.identifier.authorityChan, FTS=rp00090en_HK
dc.identifier.authorityChan, PLY=rp00093en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1016/j.rcim.2005.04.002en_HK
dc.identifier.scopuseid_2-s2.0-32544437401en_HK
dc.identifier.hkuros119203en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-32544437401&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume22en_HK
dc.identifier.issue3en_HK
dc.identifier.spage217en_HK
dc.identifier.epage238en_HK
dc.identifier.isiWOS:000235822600003-
dc.publisher.placeUnited Kingdomen_HK
dc.identifier.scopusauthoridChan, FTS=7202586517en_HK
dc.identifier.scopusauthoridLau, KW=36722692600en_HK
dc.identifier.scopusauthoridChan, PLY=7403540482en_HK
dc.identifier.scopusauthoridChoy, KL=7005477047en_HK

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